Genetic Algorithm(GA) has been applied to Block Matching Algorithm (BMA) and demonstrates positively its capability in BMA. Four-step genetic search (465) has been proposed recently [I]. The mean square error (MSE) performance of 4GS is close to FS. The computational cost of 4GS is close to the well known three-step search (SSS).Realization of 4GS can be applied in video encoding hardware. Practical implementation issues of 4GS by using FPGA will be discussed. Since FPGA is reconfigurable device, the configuration of 4GS module can be changed as frame size changed.

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In order to design the speed controller of the DC motor system, firstly, parameters estimation of the system must be preceded. In this paper, we proposed the application of genetic algorithm(GA) optimization in estimating the parameters of DC motor. Estimated models are considered both first and second order models, and each estimated model is optimized by minimizing three different types of the evaluation function of GA. Also, GA is imported in comparison with estimation result of numerical analysis method because of its power in searching entire solution space with more probability of finding the global optimum. Data for parameter estimation is acquired from input and output signals of the actual experiment device and the butterworth filter also designs for removing noise in the signals. Finally comparison between real data of the actual device and estimated models is presented to indicate effectiveness and resolution of proposed identification method.

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